Analysis and synthesis of human motion from external measurements

The structures observed in humans are being progressively applied to the theoretical approaches developed in robotics. To gain insight to the intricate mechanism of human motion, researchers sometimes use imaging technology to record the trajectories of humans performing various tasks. From these observations, they are able to estimate the forces and moments at each joint by an inverse dynamics computation. This problem is conceptually simple; however, in practice, the inverse solution requires the calculation of higher order derivatives of experimental observations contaminated by noise. The errors due to differentiation results in erroneous joint force and moment calculations. This paper provide a control theoretic framework for analyzing human motion which avoids derivative computations. The method is also suitable for synthesis of stable controllers for robotic and 'biorobic' applications which require tracking a desired reference trajectory under different loading conditions.